Mode Control Of Robot Manipulators Research Articles

Adaptive funnel fast nonsingular terminal sliding mode control for robotic manipulators with dynamic uncertainties

In this paper, a novel adaptive funnel fast nonsingular terminal sliding mode control for robotic manipulators with dynamic uncertainties is proposed. A modified funnel variable is utilized to transform the tracking error fall within funnel boundary, which improves the transient and steady-state tracking performance of robotic manipulators. Based on the transformed error, a novel funnel fast nonsingular terminal sliding mode surface is developed and a sliding mode control law is designed to stabilize the closed-loop system and achieve high tracking precision. An adaptive update law combined with the sliding mode surface is designed to deal with uncertainties and external disturbances where their upper bounds are unknown in practical cases. The stability and finite time convergence of the closed-loop system are proved by Lyapunov stability theorem. Simulation results and discussions are presented to demonstrate the effectiveness and high-precision tracking control for robotic manipulators.

Adaptive nonlinear observer–based sliding mode control of robotic manipulator for handling an unknown payload

This article presents the control synthesis of robotic manipulators with an unknown constant payload. A novel nonlinear disturbance observer with an adaptive scheme is designed to estimate the external force induced by the unknown constant payload. A general design procedure for designing the gain of the nonlinear observer is developed rather than the time-consuming trials and error to choose proper gain. The nonlinear observer gain is designed using an adaptive technique to extend the applicability of the disturbance observer. The stability of the proposed observer is established using Lyapunov method under certain conditions. The proposed nonlinear disturbance observer will be integrated with the sliding mode control to substantially alleviate the chattering problem. Also, simulation results are presented to verify the effectiveness of the proposed methods.

Observer‐based adaptive second‐order non‐singular fast terminal sliding mode controller for robotic manipulators

AbstractIn this paper, a second‐order non‐singular fast terminal sliding mode controller is proposed for robotic manipulators in the presence of uncertainties and disturbances. Adaptive control is used to obtain robustness to system uncertainties and disturbances. The improved high‐gain observer is designed to estimate the speed information, which makes the controller more applicable in practice. Theorem proof and simulations demonstrate the effectiveness of the proposed controller.

Free-Chattering Fuzzy Sliding Mode Control of Robot Manipulators with Joints Flexibility in Presence of Matched and Mismatched Uncertainties in Model Dynamic and Actuators

In this paper, a simple but effective voltage-based fuzzy sliding mode control (SMC) is proposed to control the position of a class of flexible-joints robot manipulators with n degrees of freedom in presence of matched and mismatched uncertainties related to the electrical and mechanical equations. In order to solve problems in comparison with conventional SMC, a sliding surface with the time-varying parameter is proposed which not only eliminates chattering and increases the stability of the closed loop system, but also prevents the increase of the control input voltage. Furthermore, an approach is proposed to calculate the sliding surface vector coefficients which, in presence of the existing uncertainties, guarantee the global asymptotically stability of the closed loop system. Finally, simulation and practical implementation results are presented to exhibit the helpfulness of the proposed control technique compared to the previous methods.

Non-singular Terminal Sliding Mode Control of Robot Manipulators with $$H_\infty $$ Trajectory Tracking Performance

This paper develops a novel non-singular terminal sliding mode control scheme for trajectory tracking of robot manipulators in the presence of external disturbances and uncertainties. Firstly, with the introduction of two nonlinear terms, a newly terminal sliding surface is designed. Then utilizing this sliding surface, a novel non-singular terminal sliding mode controller is proposed to eliminate the reaching interval, singularity issue and subsequently with this controller, the finite time error convergence is also assured. In the proposed controller, radial basis function neural network is employed to approximate highly uncertain nonlinear dynamics of robot manipulators using update laws derived with Lyapunov approach. Meanwhile, the effects of approximation errors are attenuated with $$H_\infty $$ performance criterion by introducing a robust term into the controller. As a result of proposed approach, asymptotic convergence of tracking errors is achieved within finite time and the approximation errors are attenuated to desired levels. The numerical simulation result shows the effectiveness of proposed controller for the case of microbot type robot manipulator.

RBFNN-based nonsingular fast terminal sliding mode control for robotic manipulators including actuator dynamics

To achieve robust finite-time trajectory tracking control, this paper proposes a novel neural-network-based nonsingular fast terminal sliding mode (NFTSM) control strategy for n-link robotic manipulators including actuator dynamics, subject to the model uncertainty and external disturbances. The suggested NFTSM control method can improve the finite-time convergence rate of system states, owing to the introduction of nonlinear item on the sliding surface. In addition, the singular problem is settled via introducing a saturation function into the control signal. In this control scheme, the precise dynamics of the robot system are unknown completely. Considering that the radial basis function neural network (RBFNN) has a fast study convergence speed and great approximation ability, three RBFNNs are utilized to estimate the manipulator-actuator dynamic parameters, along with an adaptive weight update law. Meanwhile, by designing robust control items, the approximation errors of RBFNNs are compensated, and the external disturbances are suppressed. Then, the finite-time stability of the controlled system is proved by Lyapunov stability theory. Finally, the proposed control approach is employed to a two-link robotic manipulator. The simulation results verified the effectiveness of the proposed control method.

Adaptive back stepping fast terminal sliding mode control of robot manipulators actuated by pneumatic artificial muscles: continuum modelling, dynamic formulation and controller design

Pneumatic Artificial Muscles (PAMs) also called braided pneumatic actuators were invented by Mckibben to help the Polio patients. When the internal bladder is pressurized the actuator gets shorter which can produce a tensile force. PAMs are widely used in bio robotic as well as industrial, medical and rehabilitation robotic applications due to their salient advantages such as high power to weight ratio, flexibility and low cost. However, PAMs exhibit highly non-linear characteristics due to nonlinear mechanical properties of the inner tube and geometrically complex behavior of the outer shell. To use PAMs in engineering applications it is necessary to have an accurate relationship between produced axial force, contraction ratio and applied internal pressure. In this work, a continuum mechanics based model is extended to calculate actuation force of PAMs which is essential in calculation of the required internal pressure as the input signal for control of PAM-based systems. Moreover, dynamic model of a 2-link robot manipulator actuated by PAMs is presented and an adaptive back stepping fast terminal sliding mode controller is applied. Robustness of the utilized method against external disturbances and parameter uncertainties is also investigated. Comparing the model results with experimental data, it is observed the model well predicts mechanical behavior of PAMs. Furthermore, positions and tracking errors are compared with results of an adaptive sliding mode controller. Simulation results obviously demonstrate fast and accurate tracking performance of the applied controller. The developed model can be widely used in design of rehabilitation and also industrial robotic systems.

Adaptive second-order fast nonsingular terminal sliding mode control for robotic manipulators

This paper presents an adaptive chattering-free sliding mode controller for trajectory tracking of robotic manipulators in the presence of external disturbances and inertia uncertainties. To achieve fast convergence and desirable tracking precision, a second-order fast nonsingular terminal sliding mode (SOFNTSM) controller is designed to guarantee system performance and robust stability. Chattering is eliminated using continuous control law due to high-frequency switching terms contained in the first derivative of actual control signals. Meanwhile, uncertainties are compensated by introducing the adaptive technique, whose prior knowledge about upper bound is not required. Finally, simulation results validate the effectiveness of the proposed control scheme.

Improvement of Tracking Control of a Sliding Mode Controller for Robot Manipulators by a Neural Network

This article presents a neural network control technique to improve the tracking performance of a robot manipulator controlled by the sliding mode control method in a non-model-based framework. The sliding mode controller is a typical nonlinear controller that has been well developed in theory and used in many applications due to its simplicity and practicality. Selection of the gain of the nonlinear function plays an important role in performance as well as stability. When the sliding mode controller is used for the non model-based configuration in robot control, the nonlinear gain should be selected large enough to guarantee the stability. Since the appropriate selection of the gain value is essential and difficult in the sliding mode control framework, a neural network compensator is introduced at the trajectory level to help the fixed gain deal with the stability and performance more intelligently. Stability of the proposed control scheme is analyzed. Simulation studies of following the Cartesian trajectory for a three-link rotary robot manipulator are conducted to confirm the control improvement by the neural network.

Adaptive Sliding Mode Control of Robot Manipulator Based on Second Order Approximation Accuracy and Decomposed Fuzzy Compensator

A kind of adaptive sliding mode control scheme for tracking control of robot manipulator which has structured uncertainties and unstructured uncertainties is proposed in this paper. Multi-input Multi-output fuzzy logical system (FLS) is used as a compensator in the control law to compensate all the uncertainties. To reduce the number of the fuzzy rules and the burden of the computation, we design FLS based on second order approximation theorem which can approximate the uncertain function with less fuzzy rules at arbitrary precision than traditional FLS. Besides, to further reduce the number of the fuzzy rules and the amount of calculation, a new decomposed fuzzy logical system based on the decomposition of membership function is proposed. From the simulation results we can see that the control scheme and the fuzzy compensator proposed in this paper can perform fairly.

Backstepping terminal sliding mode control of robot manipulator using radial basis functional neural networks

This paper examines an observer-based backstepping terminal sliding mode controller (BTSMC) for 3 degrees of freedom overhead transmission line de-icing robot manipulator (OTDIRM). The control law for tracking of the OTDIRM is formulated by the combination of BTSMC and neural network (NN) based approximation. For the precise trajectory tracking performance and enhanced disturbance rejection, NN-based adaptive observer backstepping terminal sliding mode control (NNAOBTSMC) is developed. To obviate local minima problem, the weights of both NN observer and NN approximator are adjusted off-line using particle swarm optimization. The radial basis function neural network-based observer is used to estimate tracking position and velocity vectors of the OTDIRM. The stability of the proposed control methods is verified with the Lyapunov stability theorem. Finally, the robustness of the proposed NNAOBTSMC is checked against input disturbances and uncertainties.

High-speed nonsingular terminal switched sliding mode control of robot manipulators

This paper proposes a high-speed nonsingular terminal switched sliding mode control U+0028 HNT-SSMC U+0029 strategy for robot manipulators. The proposed approach enhances the control system performance by switching among appropriate sliding mode controllers according to different control demands in different regions of the state space. It is shown that the highspeed nonsingular terminal switched sliding mode U+0028 HNT-SSM U+0029 which is the representation of different control demands and enforced by the HNT-SSMC has the property of global highspeed convergence compared with the nonsingular fast terminal sliding mode U+0028 NFTSM U+0029, and provides the global non-singularity. The simulation study of an application example is carried out to validate the effectiveness of the proposed strategy.

Comments on ‘A new terminal sliding mode control for robotic manipulators’

ABSTRACTIn this article, we give some comments on the article ‘A new terminal sliding mode control for robotic manipulators’. The article presents a new terminal sliding mode control approach for global finite-time tracking of robotic manipulators. We point out a serious error occurred through the article, leading to the ineffectiveness of the proposed approach. A correction is proposed. Comparisons are presented.

A novel self-adaptive modified bat fuzzy sliding mode control of robot manipulator in presence of uncertainties in task space

SUMMARYIn this paper, an optimal fuzzy sliding mode controller has been designed for controlling the end-effector position in the task space. In the proposed control, feedback linearization method, sliding mode control, first-order fuzzy TSK system and optimization algorithm are utilized. In the proposed controller, a novel heuristic algorithm namely self-adaptive modified bat algorithm (SAMBA) is employed. To achieve an optimal performance, the parameters of the proposed controller as well as the input membership functions are optimized by SAMBA simultaneously. In this method, the bounds of structural and non-structural uncertainties are reduced by using feedback linearization method, and to overcome the remaining uncertainties, sliding mode control is employed. Mathematical proof demonstrates that the closed loop system with the proposed control has global asymptotic stability. The presence of sliding mode control gives rise to the adverse phenomenon of chattering in the end-effector position tracking in the task space. Subsequently, to prevent the occurrence of chattering in control input, a first-order TSK fuzzy approximator is utilized. Finally, to determine the fuzzy sliding mode controller coefficients, the optimization algorithm of Self-Adaptive Modified Bat is employed. To investigate the performance of the proposed control, a two-degree-of-freedom manipulator is used as a case study. The simulation results indicate the favorable performance of the proposed method.

A Novel Finite Time Sliding Mode Control for Robotic Manipulators

A novel robust control law with finite time convergence for rigid robotic manipulators is proposed in this paper. The whole control process is divided into two phases, i.e., the error correction phase and the steady tracking phase. Firstly, a novel time-varying sliding mode control (TVSMC) method is developed in the first phase to ensure the tracking error converge to zero at the desired time. Subsequently, the nonsingular terminal sliding mode control (NTSMC) technique is employed to keep the tracking error maintaining zero during the second phase. The associated control commands are free from singularity and convenient for practical implementation. Besides, the convergence rate can be tuned via appropriate parameter adjustment. By the virtue of global sliding mode, the system is global robust against the external disturbances and parametric uncertainties. Numerical simulations are presented to validate the effectiveness of the proposed control law.

Time-varying nonsingular terminal sliding mode control for robot manipulators

In this paper, a time-varying nonsingular terminal sliding mode (T-NTSM) controller is proposed and modified for the rigid robot manipulators with parametric uncertainties and external disturbances. First, in order to eliminate the reaching phase, a novel T-NTSM manifold is proposed by incorporating a piecewise defined function of time into a nonsingular terminal sliding mode manifold. Then a T-NTSM controller is derived from such a sliding surface, by which the robustness is ensured during the entire response of the system, and the convergence time can be chosen in advance. An especially effective method is provided for parameter selection to meet the convergence time requirement. Subsequently, a modified T-NTSM controller is proposed to enhance performance by introducing a time-varying gain in the proposed T-NTSM manifold. The modified controller ensures faster convergence rate and smaller control input amplitude. Finally, the proposed controllers are applied in the control of a two-link manipulator. All of the simulation results demonstrate the effectiveness of the proposed control methods.

Adaptive second order terminal sliding mode controller for robotic manipulators

In this paper an adaptive second order terminal sliding mode (SOTSM) controller is proposed for controlling robotic manipulators. Instead of the normal control input, its time derivative is used in the proposed controller. The discontinuous sign function is contained in the derivative control and the actual control obtained after integration is continuous and hence chatterless. An adaptive tuning method is utilized to deal with the system uncertainties whose upper bounds are not required to be known in advance. The performance of the proposed control strategy is evaluated through the control of a two-link rigid robotic manipulator. Simulation results demonstrate the effectiveness of the proposed control method.

Minimal Resource Allocating Networks for Discrete Time Sliding Mode Control of Robotic Manipulators

This paper presents a discrete-time sliding mode control based on neural networks designed for robotic manipulators. Radial basis function neural networks are used to learn about uncertainties affecting the system. The online learning algorithm combines the growing criterion and the pruning strategy of the minimal resource allocating network technique with an adaptive extended Kalman filter to update all the parameters of the networks. A method to improve the run-time performance for the real-time implementation of the learning algorithm has been considered. The analysis of the control stability is given and the controller is evaluated on the ERICC robot arm. Experiments show that the proposed controller produces good trajectory tracking performance and it is robust in the presence of model inaccuracies, disturbances and payload perturbations.

Fuzzy Sliding Mode Control of Robotic Manipulators With Kinematic and Dynamic Uncertainties

Sliding mode control is a very attractive control scheme with strong robustness to structured and unstructured uncertainties as well as to external disturbances. In this paper, a robust fuzzy sliding mode controller, which is combined with an adaptive fuzzy logic system, is proposed to improve the control performance of the robotic manipulator with kinematic and dynamic uncertainties. In this controller, the sliding mode control is employed to improve the control accuracy and the robustness of the robotic manipulator, and the fuzzy logic control is adopted to approximate various uncertainties and to eliminate the chattering without the help of any prior knowledge of system uncertainties. The effectiveness of the proposed controller is then verified by the simulations on a 2-DOF (degrees of freedom) robotic manipulator and the experiments on an SCARA robot with four degrees of freedom. Simulated and experimental results indicate that the proposed controller is effective in the robust tracking of the robotic manipulator with kinematic and dynamic uncertainties.

Discrete time sliding mode control of robotic manipulators: Development and experimental validation

This paper presents a robust discrete-time sliding mode control coupled with an uncertainty estimator designed for planar robotic manipulators. Experimental evidence shows satisfactory trajectory tracking performances and noticeable robustness in the presence of model inaccuracies, disturbances and payload perturbations. Ultimate boundedness of the tracking errors is proved, as well as boundedness of the estimation error with arbitrary precision.